Skip to main content
Glama
enriquecatala

mcp-lightrag

query_knowledge_graph

Search a knowledge graph using various strategies—semantic, keyword, hybrid—to answer questions from indexed data.

Instructions

Search the knowledge graph for information using various strategies. Ideal for answering questions based on indexed data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe question or search query to execute against the knowledge base
search_modeNoSearch strategy to use: 'mix' (recommended for comprehensive results), 'semantic' (vector search), 'keyword' (exact match), 'global' (broad context), 'hybrid' (semantic + keyword), 'local' (specific context), 'naive' (simple)mix
limitNoMaximum number of result items/paragraphs to retrieve
context_onlyNoIf True, returns only the raw context data without LLM generation
prompt_onlyNoIf True, returns only the constructed LLM prompt without executing it to the LLM
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose all behaviors. It fails to state whether the tool is read-only, has side effects, requires authentication, or any rate limits. The description is vague about the output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences. It front-loads the main purpose and adds a usage hint. No unnecessary words, though it could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters, no output schema, and many sibling tools, the description is too minimal. It lacks information about output format, data scope, and expected behavior. The agent may not fully understand what the tool returns or how to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents parameters. The description's mention of 'various strategies' adds no new meaning beyond the schema's detailed explanation of search_mode. It does not improve or worsen parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: searching the knowledge graph for information using various strategies. It is distinct from sibling tools like 'find_document', but does not explicitly differentiate itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says it's 'Ideal for answering questions based on indexed data,' providing a usage context. However, it gives no when-not-to-use instructions or comparisons with alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/enriquecatala/mcp-lightrag'

If you have feedback or need assistance with the MCP directory API, please join our Discord server